In today’s world consumers want to know if the companies they do business with are acting in a sustainable manner. In addition, the environment is teetering dangerously close to the point of no return when it comes to carbon emissions, and manufacturers are increasingly expected to reduce waste and energy usage, while making the highest quality products possible.
This is a tall order, but it is one that every company within the manufacturing sector must meet, including the tissue and nonwovens ones.
One of the issues that has to be addressed to achieve our objective is the loss of productivity on a production line, and one of the top reasons for this is machine downtime.
What is Downtime
Downtime occur when a machine is unproductive for reasons that are outside of the control of workers or management. During this idle time, workers are generally waiting while a machine is being serviced or it is offline, and the production can continue only if the idle machine can be bypassed.
Impact of machine Downtimes
When machinery on the production line is down, the cost for a factory is between 5% and 20% of its productivity capacity. Not only that but an estimated 80% of industrial facilities are not able to accurately estimate the scope of their machine downtime.
It is common for facilities to underestimate the cost of these machine downtime by as much as 200% to 300%, and when it comes to meeting production targets and profit margins this is unacceptable. The starting point for a tissue and nonwovens plant is to gain an understanding of their machinery and what causes idle times to occur.
Causes of Downtime
Downtime can be either planned or unplanned. The former are generally for regular machine maintenance, software and hardware upgrades, inspections, and anything else required for the upkeep of the machine, while the latter are are generally due to machine breakage or malfunction, software or hardware errors, or overall poor performance. It goes without saying that unplanned downtimes are costly and obviously more disruptive because they can cause significant interruption to productivity.
According to the American Productivity and Quality Center (APQC) unplanned downtimes are responsible for a loss of between $0.40 and $1.20 for every $20, and it is therefore vitally important for every manufacturing company to avoid these phenomena.
Reducing and Optimizing Machine Downtime: 4 key tools
The Industry 4.0 technology is the answer to these problems.
Industry 4.0 has brought machine communication and automation to a point at which data can be collected from every machine of the production line in real-time and subsequently analyze these data in isolation or in relation to those coming from every other machine.
To accomplish this, there are a number of tools that tissue and nonwovens companies need to have in place.
1. Machine Sensors
Each machine on the production line will be equipped with numerous sensors in order to collect data in real-time during operation. These data will reveal, for example, the operating state of the machine, its speed, vibrations and other environmental factors, such as temperature and humidity, that the human senses cannot detect.
2. The Cloud
Thanks to Cloud computing, the various machines will be connected wirelessly to each other, as well as to computers and mobile devices used by workers on the production line and in head office. This will allow for the remote collection and analysis of data from any production line in any plant.
The data that are sent across the cloud will need to be integrated into a single platform capable of analysing them and to allow both a bird’s eye view of the production line and a closeup view of the operation of any individual machine.
This data integration is incredibly important in light of the fact that the machines on production lines tend to have their own unique software, isolating their data from those of the other machines and from every other data related to business operations.
4. AI/Machine Learning
Finally, artificial intelligence and machine learning will be capable of analyzing the data coming in, recognize anomalous ones and act accordingly. Machine learning will use algorithms to understand anomalous readings and to schedule predictive maintenance. These tools are key in improving machine performance and reducing unplanned downtime or avoiding it altogether.
Reduce Downtime and Boost Productivity with Industry 4.0
We have seen that, despite the pressures to which companies are subjected, there is nowadays a technology capable of minimizing or eliminating machine downtime.
Thanks to these tools you will be able to gather all the data sent by disparate machines in any production line, integrate them, analyze them, interpret those analyses, and implement automated measures to ensure machines are always running at peak efficiency.
For more information on how to keep your tissue and nonwovens production line operating at peak efficiency, download our free eBook “5 Industry 4.0 Tools that Boost Productivity in the Tissue Paper and Nonwovens Industry”!